Case studies

How it looks in practice.

Four illustrative scenarios — one per market. They show the shape of the work: data in, qualified opportunities out, a clean introduction made.

Illustrative

Ellabook’s cross-border arrangement is new, so the scenarios below are illustrative and anonymised — they demonstrate the capability and the workflow, not actual transactions. Figures are operational (how the data moved), never investment returns.

Hong Kong Illustrative
Boutique advisory firm

A firm with a long but under-used client list wanted to know which relationships were worth re-engaging. Our AI scored the book and surfaced a cluster of cross-border clients whose needs matched a partner’s service — and a person reviewed each before any contact.

Introduced to a licensed partner who handled everything regulated.

11,800Records analysed
320Dormant clients re-surfaced
16Introductions made

Illustrative scenario. Figures are representative, not actual results, and do not describe investment returns.

China Illustrative
Corporate services provider

A provider serving mainland founders wanted to spot which clients had genuine cross-border needs without trawling the list by hand. The engine flagged a focused set of qualified signals; the rest were left untouched.

Matched to a partner in the destination market and introduced.

6,400Records analysed
72Cross-border signals flagged
9Introductions made

Illustrative scenario. Figures are representative, not actual results, and do not describe investment returns.

New Zealand Illustrative
Mortgage brokerage (Plaxo)

Through the Plaxo brand, a brokerage wanted to re-surface past enquiries that had gone cold. AI ranked the back-book by current fit, and the team worked only the strongest, freshest matches.

Connected to the right lending partner for each case.

4,900Back-book re-scored
140Hot matches surfaced
3 wksMedian cycle

Illustrative scenario. Figures are representative, not actual results, and do not describe investment returns.

Australia Illustrative
Lending introducer (OneLend)

A OneLend-aligned introducer wanted to focus a small team on the highest-fit opportunities in a large book. The engine did the triage; people did the judgement and the relationships.

Referred to licensed lenders who carried out the regulated work.

8,200Records analysed
86%Book left untouched
19Introductions made

Illustrative scenario. Figures are representative, not actual results, and do not describe investment returns.

Curious what’s hidden in your own client book?

We’ll walk you through the workflow and exactly where our role ends and a licensed partner’s begins.